Modern inventory systems, such as those in mail order warehouses, supply chain distribution centers, airport luggage systems, and custom-order manufacturing facilities, face significant challenges in responding to requests for inventory items. As inventory systems grow, the challenges of simultaneously completing a large number of inventory-related tasks become non-trivial. In inventory systems tasked with responding to large numbers of diverse inventory requests, inefficient utilization of system resources, including space, equipment, and manpower, can result in lower throughput, unacceptably long response times, an ever-increasing backlog of unfinished tasks, and, in general, poor system performance.
In modern inventory systems that have incorporated robotic devices to assist with inventory related tasks, the process of tracking these robotic devices becomes a complex, technical problem as well. For example, a robotic device may be tracked at a particular location in a warehouse. Physical attributes of the warehouse may hinder the identification of the robotic device, despite several sensors or data used to track the device. As a result, any improved technical changes to functionality of the robotic devices may not be fully realized due to the limitations of physical attributes of the warehouse or inefficient utilization of other processes, limiting the ability of the system to accommodate fluctuations in system throughput.